GitHub

K-Paths: Reasoning over Graph Paths for Drug Repurposing and Drug Interaction Prediction.

K-Paths is a retrieval framework that extracts structured, diverse, and biologically meaningful paths from knowledge graphs (KGs). These extracted paths enables large language models (LLMs) and graph ...
Deep Learning with Yacine on MSN

Build k-nearest neighbors from scratch in Python – step by step tutorial

Learn how to implement the K-Nearest Neighbors (KNN) algorithm from scratch in Python! This tutorial covers the theory, ...
GitHub

Lightweight Nearest Neighbors with Flexible Backends

Vicinity is a light-weight, low-dependency vector store. It provides a simple and intuitive interface for nearest neighbor search, with support for different backends and evaluation. There are many ...
IEEE

Density Peaks Clustering Based on Label Propagation and K-Mutual-Nearest Neighbors

Abstract: The density peaks clustering algorithm is one of the density-based clustering algorithms. This algorithm has several advantages, including not requiring a preset number of clusters, ...
The Guardian

‘Better out than in’: why a South Yorkshire charity wants people to speak their mind

Who Is Your Neighbour? lets people talk in constructive, thoughtful ways to offer an antidote to division and despair Donate to the charity appeal here It was a filthy day in Rotherham as Storm Bram ...
The New York Times

When Did Everything Become ‘K-Shaped’?

What started as a term to describe the pandemic recovery has become a catchall in these anxious economic times. By Lora Kelley Holiday spending this year is expected to surpass $1 trillion for the ...
IEEE

An Ensemble for Automatic Time Series Forecasting With K-Nearest Neighbors

Abstract: In this paper a novel approach for automatically configuring a k-nearest neighbors regressor for univariate time series forecasting is presented. The approach uses an ensemble consisting of ...